tensorflow-plot | TensorFlow Matplotlib as TF ops | Machine Learning library

by wookayin Python Version: 0.3.2 License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | tensorflow-plot Summary

tensorflow-plot is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. tensorflow-plot has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install tensorflow-plot' or download it from GitHub, PyPI.

There are two main ways of using tfplot: (i) Use as TF op, and (ii) Manually add summary protos.

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tensorflow-plot has a low active ecosystem.

It has 288 star(s) with 41 fork(s). There are 14 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 10 have been closed. On average issues are closed in 79 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tensorflow-plot is 0.3.2

Quality

tensorflow-plot has 0 bugs and 14 code smells.

Security

tensorflow-plot has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

tensorflow-plot code analysis shows 0 unresolved vulnerabilities.

There are 2 security hotspots that need review.

License

tensorflow-plot is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

tensorflow-plot releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

tensorflow-plot saves you 471 person hours of effort in developing the same functionality from scratch.

It has 1111 lines of code, 85 functions and 16 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed tensorflow-plot and discovered the below as its top functions. This is intended to give you an instant insight into tensorflow-plot implemented functionality, and help decide if they suit your requirements.

Wraps tf autow autowrap func
Creates a matplotlib plot
Wrap a summary function
Create a matplotlib figure
Return the class defining a method
Merge a dictionary of keyword arguments
Clean up names
Runs Twine
Return the version string
Prints a status message
Predict a probability map
Plots a probmap of x
Returns the version string
Make a temporary directory

Get all kandi verified functions for this library.

tensorflow-plot Key Features

No Key Features are available at this moment for tensorflow-plot.

tensorflow-plot Examples and Code Snippets

No Code Snippets are available at this moment for tensorflow-plot.

Community Discussions

Trending Discussions on tensorflow-plot

Missing modules and attributes for training in TensorFlow's Object Detection API

pip search finds tensorflow, but pip install does not

QUESTION

Missing modules and attributes for training in TensorFlow's Object Detection API

Asked 2020-Feb-08 at 15:12

I'm currently attempting to train an object detection model. I'm following Gilbert Tanner's tutorial on YouTube. I am running TF version 1.9.0.

It seems as though I'm missing the necessary modules. When I run the following command:

...

ANSWER

Answered 2020-Feb-08 at 15:12

This code tf.compat.v1.GraphKeys.UPDATE_OPS is not available on Tensorflow==1.9.0, this is the same for tf.compat.v2.nn.avg_pool2d.

To have those features update your version to 1.15 with conda install tensorflow=1.15. That will match the tutorial's version. As obtained from it's repository it uses tensorflow-gpu==1.15.2.

Source https://stackoverflow.com/questions/60104249

QUESTION

pip search finds tensorflow, but pip install does not

Asked 2020-Jan-23 at 06:55

I am trying to build a Django app that would use Keras models to make recommendations. Right now I'm trying to use one custom container that would hold both Django and Keras. Here's the Dockerfile I've written.

...

ANSWER

Answered 2019-Jan-02 at 22:56

It looks like tensorflow only publishes wheels (and only up to 3.6), and Alpine linux is not manylinux1-compatible due to its use of musl instead of glibc. Because of this, pip cannot find a suitable installation candidate and fails. Your best options are probably to build from source or change your base image.

Source https://stackoverflow.com/questions/54014076

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

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Support

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